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Taxonomy: IM- Cone Beam CT: Machine learning, computer vision

PO-GePV-I-2	Short-Scan Cone-Beam Dedicated Breast CT: Self-Supervised Denoising From Single Image Z Fu1*, H Tseng1, A Karellas1, S Vedantham1,2, (1) Department of Medical Imaging, University of Arizona, Tucson, AZ, (2) Biomedical Engineering, University of Arizona, Tucson, AZ
PO-GePV-I-12	A Hybrid Scatter Correction Algorithm for CBCT to Incorporate System-Specific Information with a Deep Learning-Based Scatter Correction Algorithm H Lee*, A Lalonde, B Winey, G Sharp, H Paganetti, Massachusetts General Hospital / Harvard Medical School, Boston, MA
PO-GePV-I-18	Low-Dose Cone-Beam Dedicated Breast CT: Self-Supervised Denoising From Single Image Z Fu1*, H Tseng1, A Karellas1, S Vedantham1,2, (1) Department of Medical Imaging, University of Arizona, Tucson, AZ, (2) Department of Biomedical Imaging, University of Arizona, Tucson, AZ
PO-GePV-M-168	Feasibility Study of Deep Learning Based ITV Prediction in Cone Beam CT Images & It’s Dosimetric Study of Lung SBRT S Zhang1, Z Li2, E Yang3, Y Li4, L Zhang5, X Zheng6, J Qiu7*, (1) Department of Radiation Oncology, Huadong Hospital, Fudan University,, Shanghai, 31, CN, (2) Duke Kunshan University, Kunshan, 32, (3) Department of Radiation Oncology, Huadong Hospital, Fudan University,, Shanghai, 31, CN, (4) Department of Radiation Oncology, Huadong Hospital, Fudan University,, Shanghai, 31, CN, (5) Department of Radiation Oncology, Huadong Hospital, Fudan University,, Shanghai, 31, CN, (6) Department of Radiation Oncology, Huadong Hospital, Fudan University,, Shanghai, 31, (7) Department of Radiation Oncology, Huadong Hospital, Fudan University,, Shanghai, 31, CN
PO-GePV-M-287	A Two-Step Method to Improve Image Quality of CBCT with Phantom-Based Supervised and Patient-Based Unsupervised Learning Strategies Y Liu1,2*, X Chen1, J Zhu1, B Yang1, R Wei1, R Xiong2, H Quan2, Y Liu1, J Dai1, K Men1, (1) National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Beijing, 100021 ,CN, (2) Wuhan University, Wuhan, 430072 ,CN,
PO-GePV-M-320	TransCBCT: Improving the Image Quality of Cone-Beam Computed Tomography with Transformer X Chen1*, Y Liu1, B Yang1, J Zhu1, Y Liu1, J Dai1, K Men1, (1) National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Beijing, 100021,CN
SU-F-201-2	Improving Cone-Beam CT Auto-Segmentation Accuracy Using Cycle GANs for Domain Adaptation K Shah1*, J Shackleford1, N Kandasamy1, G Sharp2, (1) Drexel University, Philadelphia, PA, (2)Massachusetts General Hospital, Boston, MA